Welcome to the Time Series Analysis and Recommender Systems repository! This repository is a collection of resources, code examples, and tutorials to help you explore and understand the realms of time series analysis and recommender systems.
This repository aims to provide a comprehensive learning resource for both beginners and experienced data enthusiasts interested in time series analysis and recommender systems. Whether you're looking to learn the fundamentals, explore advanced techniques, or find real-world examples, you'll find something here to support your journey.
To get started with the content in this repository, follow these steps:
- Clone the repository to your local machine.
- Explore the relevant directories for time series analysis and recommender systems.
- Refer to the provided code examples, tutorials, and documentation.
In the notebooks that are related to time series, you'll find resources related to analyzing and forecasting time-dependent data. This includes introductory materials, code snippets, and practical examples for various time series analysis techniques.
In the notebooks that are related to Recommender Systems, you'll find all things related to building recommendation engines.
Contributions to this repository are welcome! If you have code examples, tutorials, datasets, or any other resources related to time series analysis or recommender systems, feel free to open a pull request.
This project is not licensed, which means you're free to use the code and content in this repository for your own projects.
Happy coding and learning!